This course is intended to serve as an advanced overview of robotics spanning
the complete autonomy loop: robot hardware, perception,
planning, and control. We will study algorithms and data structures related to
these topics, covering widely adopted, and state of the art techniques. Students
will gain hands-on experience in implementing, and extending such algorithms
using real robot data, as well as simulations.
All assignments are due at the start of the class on the day that they are
due. You may use a total of three late days in any combination over all
the assignments without penalty. Late assignments will be determined by
their submission time on Moodle. After the late days are used up, the
value of the assignment is halved for every additional day taken. You must
submit all assignments to earn a passing grade in the class.
Academic honesty and collaboration policy:
All assignments submitted by you, including your writeup and code, must be
your own, coded by you, formulated by you, and explained by you. You may
discuss the general topics of the course with anyone, and the assignment
problems, however the solution you turn in must be based entirely on your
understanding of the problem. As a rule of thumb to distinguish discussion
from plagiarism, feel free to discuss problems verbally or via temporary
written means (e.g. whiteboard), but do not share any written matter or
code. On each assignment you must list all collaborators and people you
have discussed the assignment with, and creadit all sources.
We follow the university's
Academic Honesty Policy and Procedures.